My use case is basic. I have 3 labels say positive, negative and neutral. The data for this ML model is streamed / batched. Let’s assume that each batch holds 100 samples (batch_size=100). I can clearly see that this is an online / incremental learning problem. There is a possibility that my batch may get imbalanced / skewed data samples as well.. For example, B1-B4 may have all positive and B5-B10 may contain all negative and B11-B15 may have all neutral data samples..